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Background/Objectives: The implementation of information quality value stream maps (IQ-VSMs) in food animal production systems can increase our understanding of the opportunities and challenges when using laboratory testing for antimicrobial resistance (AMR) to support antimicrobial stewardship (AMS). Our objectives were to (1) explore the implementation of information quality value stream mapping as a continuous improvement tool to inform decisions for bovine respiratory disease (BRD) management and AMS and (2) apply the information quality dimensions to identified Kaizen opportunities for the integration of laboratory data into BRD management systems to assess the appropriateness of BRD treatment plans in western Canadian feedlot production. Methods: A 'Current State' IQ-VSM outlined the processes, available information, information processing steps, and control decisions contributing to BRD management and treatment in commercial western Canadian feedlots, recognizing that laboratory BRD pathogens and AMR data are typically not part of BRD management. Results: The 'Future State' IQ-VSM incorporated Kaizen opportunities for improvement, including (i) the strategic collection of respiratory samples from representative samples of calves for laboratory analysis, regardless of clinical BRD status, (ii) compilation of laboratory data at the pen and feedlot levels, and (iii) analysis of pen- and feedlot-level laboratory data to inform the veterinarian's assessment of the appropriateness of current BRD treatment plans. Conclusions: The IQ-VSMs provided a valuable framework to visualize the integration of BRD pathogen and AMR laboratory data to support AMS and address any potential future testing requirements. [ABSTRACT FROM AUTHOR]

The methodological purpose of this article is to generate practical guidance for researchers studying complex phenomena through an adaptive case study-mixed methods (CS-MM) design. We describe CS-MM design adjustments made in response to our rapidly changeable research conditions that make complex phenomena challenging to study. We leverage Guetterman & Fetters' (2018) CS-MM design recommendations while discussing specific adaptive design practice areas and advancing new insights gleaned from an expanded 21-month timeline when compared with a previous 4-month CS-MM study. We draw upon Mike Fetters' extensive scholarly contributions while striving to continue his legacy for a better world and embodying Mike's "kind mentoring" approach in our team-based study of the complex phenomena involving the response to a public health emergency. [ABSTRACT FROM AUTHOR]

Rapid laboratory tests are urgently required to inform antimicrobial use in food animals. Our objective was to synthesize knowledge on the direct application of long-read metagenomic sequencing to respiratory samples to detect bacterial pathogens and antimicrobial resistance genes (ARGs) compared to PCR, loop-mediated isothermal amplification, and recombinase polymerase amplification. Our scoping review protocol followed the Joanna Briggs Institute and PRISMA Scoping Review reporting guidelines. Included studies reported on the direct application of these methods to respiratory samples from animals or humans to detect bacterial pathogens ±ARGs and included turnaround time (TAT) and analytical sensitivity. We excluded studies not reporting these or that were focused exclusively on bioinformatics. We identified 5,636 unique articles from 5 databases. Two-reviewer screening excluded 3,964, 788, and 784 articles at 3 levels, leaving 100 articles (19 animal and 81 human), of which only 7 studied long-read sequencing (only 1 in animals). Thirty-two studies investigated ARGs (only one in animals). Reported TATs ranged from minutes to 2 d; steps did not always include sample collection to results, and analytical sensitivity varied by study. Our review reveals a knowledge gap in research for the direct detection of bacterial respiratory pathogens and ARGs in animals using long-read metagenomic sequencing. There is an opportunity to harness the rapid development in this space to detect multiple pathogens and ARGs on a single sequencing run. Long-read metagenomic sequencing tools show potential to address the urgent need for research into rapid tests to support antimicrobial stewardship in food animal production. [ABSTRACT FROM AUTHOR]

Bovine respiratory disease (BRD) is an important health and economic burden to the cattle industry worldwide. Three bacterial pathogens frequently associated with BRD (Mannheimia haemolytica, Pasteurella multocida, and Histophilus somni) can possess integrative and conjugative elements (ICEs), a diverse group of mobile genetic elements that acquire antimicrobial resistance (AMR) genes (ARGs) and decrease the therapeutic efficacy of antimicrobial drugs. We developed a duplex recombinase polymerase amplification (RPA) assay to detect up to two variants of ICEs in these Pasteurellaceae. Whole genome sequence analysis of M. haemolytica, P. multocida, and H. somni isolates harbouring ICEs revealed the presence of tnpA or ebrB next to tet(H), a conserved ARG that is frequently detected in ICEs within BRD-associated bacteria. This real-time multiplex RPA assay targeted both ICE variants simultaneously, denoted as tetH_tnpA and tetH_ebrB, with a limit of detection (LOD) of 29 (95% CI [23, 46]) and 38 genome copies (95% CI [30, 59]), respectively. DNA was extracted from 100 deep nasopharyngeal swabs collected from feedlot cattle on arrival. Samples were tested for ICEs using a real-time multiplex RPA assay, and for M. haemolytica, P. multocida, H. somni, and Mycoplasma bovis using both culture methods and RPA. The assay provided sensitive and accurate identification of ICEs in extracted DNA, providing a useful molecular tool for timely detection of potential risk factors associated with the development of antimicrobial-resistant BRD in feedlot cattle., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024. Published by Elsevier B.V.)